Design and development of mixed integer programming model for scheduling tasks through artificial intelligence

Smart manufacturing is the way to put together consumer aspirations to execute multiple goals as well as improve the performance metrics, such as tools utilization rate, quality of the product, and efficiency of the system. Several researchers focused mainly on allocation of resources, machines schedule, vehicle systems, and tools taking into consideration of transportation time and tools between machines to get an optimal sequence that minimizes operational completion time in a multi-machine and vehicle. To enhance the system performance soft computing is the trendiest skill for task scheduling with a competent algorithm. Hence, this paper examines the task scheduling strategy in the smart manufacturing scenario based on a hybrid heuristic algorithm. It solves the problem of terminal devices with limited resources. To achieve objectives in job scheduling it is imperative way to organize end-user needs in an order and tools to save energy. Also tested significant differences among algorithms and the number of jobs with an analysis of variance (ANOVA). Finally, the task scheduling with the proposed algorithm indicates improved performance.